Peking University's most powerful open source aiXcoder-7B code model is designed for enterprise-level software development scenarios

In today's era of rapid technological development, AI code generation technology is gradually becoming a hot topic in the field of software development. Although AI performs well in solving programming problems, its application in real enterprise development environments does not seem to be ideal. To solve this problem, the aiXcoder team has launched a new open sourceCode Big Model——aiXcoder-7B Base version, designed for enterprise-level software development scenarios.

aiXcoder-7B Base is a large code model with 7 billion parameters, but its performance should not be underestimated. On the three major benchmarks HumanEval, MBPP, and MultiPL-E, aiXcoder-7B even outperformed the Codellama model with 34 billion parameters. This achievement marks a milestone for aiXcoder-7B among the large code models with tens of billions of parameters.StrongestEspecially in terms of code generation and completion capabilities and cross-file capabilities in real development scenarios, it has achieved industry-leading results.

Peking University's most powerful open source aiXcoder-7B code model is designed for enterprise-level software development scenarios

Project address: https://github.com/aixcoder-plugin/aiXcoder-7B

The highlight of aiXcoder-7B Base is its adaptability to enterprise-level software projects. It can not only handle algorithm questions in mainstream evaluation sets, but also perform well in multi-file complex code scenarios. The code generation and completion capabilities of aiXcoder-7B, including the generation of complete method blocks, conditional judgment blocks, loop processing blocks, and exception catching blocks, have been tested in practice, proving its practicality in real development environments.

In addition, aiXcoder-7B Base prefers to use shorter codes to complete tasks when completing code. This "beauty of simplicity" not only makes the code easier to understand, but also makes it easier to check for bugs. This feature is particularly important for enterprises because it means lower maintenance costs and higher code quality.

The original intention of the aiXcoder team to open source this model is to help developers reduce their workload and promote the efficiency and quality of enterprise software development. The open source of aiXcoder-7B Base version means that enterprises can easily carry out private deployment and personalized customization to adapt to their own software development frameworks and API libraries. In the future, the aiXcoder team also plans to combine multiple 7B models into a solution through the MoE architecture to meet the personalized needs of different enterprises.

The aiXcoder team was incubated by the Institute of Software Engineering of Peking University and has been researching code generation technology since 2013.TopMore than 100 related papers were published at the conference and won the ACM Outstanding Paper Award many times. From the initial aiXcoder1.0 to the current aiXcoder-7B Base version, the team has continuously launched innovative products, leading the development of intelligent programming tools.

The birth of aiXcoder-7B Base is not only a symbol of technological breakthrough, but also a sign of the acceleration of software development automation. It not only improves the efficiency and quality of software development, but also reshapes the ecology of the technology industry and leads the trend of future development. With the increasing capabilities of code big models, we have reason to believe that aiXcoder-7B will bring more innovative potential to programmers and promote the wave of programming automation forward.

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